000			03870 am a22003013u 4500
042			_adc
100	1	0	_aDixon, William G _eauthor _93030
700	1	0	_avan der Veer, Sabine N _eauthor _93031
700	1	0	_aAli, Syed Mustafa _eauthor _93032
700	1	0	_aLaidlaw, Lynn _eauthor _93033
700	1	0	_aDobson, Richard JB _eauthor _93034
700	1	0	_aSudlow, Cathie _eauthor _93035
700	1	0	_aChico, Tim _eauthor _93036
700	1	0	_aMacArthur, Jacqueline AL _eauthor _93037
700	1	0	_aDoherty, Aiden _eauthor _93038
245	0	0	_aCharting a course for smartphones and wearables to transform population health research
260			_c2023-02-07.
500			_a/pmc/articles/PMC7614184/
500			_a/pubmed/36749628
520			_aThe use of data from smartphones and wearable devices has huge potential for population health research given high device ownership, the range of novel health-relevant data types available from consumer devices, and the frequency and duration over which data are, or could be, collected. Yet the uptake and success of large-scale mobile health research in the last decade has not matched the hyped opportunity. We make the argument that digital person-generated health data is required and necessary to answer many top priority research questions through illustrative examples taken from the James Lind Alliance Priority Setting Partnership. We then summarise the findings from two UK initiatives that considered the challenges and possible solutions for what needs to be done, and in what way, to realise the future opportunities of digital person-generated health data for clinically important population health research. Examples of important areas to be addressed to advance the field include digital inequality and addressing possible selection bias, easy access for researchers to the appropriate data collection tools including how best to harmonise data items, analysis methodology for time series data, methods for patient and public involvement and engagement to optimise recruitment, retention and public trust, and providing greater control of their data to research participants. There is also a major opportunity through the linkage of digital persongenerated health data to routinely-collected data to support novel population health research, bringing together clinician-reported and patient-reported measures. We recognise that well conducted studies need a wide range of diverse challenges to be skilfully addressed in unison: for example, epidemiology, data science and biostatistics, psychometrics, behavioural and social science, software engineering, user interface design, information governance, data management and patient and public involvement and engagement. Consequently, progress would be accelerated by the establishment of a new interdisciplinary community where all relevant and necessary skills are brought together to allow excellence throughout the lifecycle of a research study. This will require a partnership of diverse people, of methods and of technology. Get this right and the synergy has the potential to transform many millions of people's lives for the better.
540			_a
540			_ahttps://creativecommons.org/licenses/by/4.0/This is a privileged document currently under peer-review/community review. Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review purposes only. While the final peer-reviewed paper may be licensed under a CC BY license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposeshttps://creativecommons.org/licenses/by/4.0/.
546			_aen
690			_aArticle
655	7		_aText _2local
786	0		_nJ Med Internet Res
856	4	1	_uhttp://dx.doi.org/10.2196/preprints.42449 _zConnect to this object online.
999			_c2403 _d2403